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Welcome

Get up and running with ClyptQ Trading Engine quickly. This guide will help you set up your development environment and run your first backtest.
1

Install ClyptQ

Install the ClyptQ package using pip:
pip install clyptq
Requires Python 3.9+ and pip. We recommend using a virtual environment.
2

Set up environment variables

Create a .env file in your project directory:
# Environment
CLYPTQ_ENV=dev  # dev, prod, kernel

# API Keys (optional for getting started)
BINANCE_API_KEY=your_api_key
BINANCE_API_SECRET=your_api_secret
For local development, you can start without API keys using sample data.
3

Create your first strategy

Create a simple momentum crossover strategy:
from clyptq.system.graph import ComputeGraph, Input
from clyptq.operators.indicator import SMA
from clyptq.operators.signal import CrossoverAlpha

# Create compute graph
graph = ComputeGraph()

# Add indicators
sma_fast = graph.add_node("sma_fast",
    SMA(Input("close", lookback=10), span=10)
)
sma_slow = graph.add_node("sma_slow",
    SMA(Input("close", lookback=50), span=50)
)

# Generate signal
signal = graph.add_node("signal",
    CrossoverAlpha(
        Input("sma_fast", lookback=1),
        Input("sma_slow", lookback=1)
    )
)
4

Run a backtest

Configure and run your first backtest:
from clyptq.apps.trading.spec import TradingSpec, StrategySpec
from clyptq.apps.trading import TradingDriver

# Create trading spec
spec = TradingSpec(
    strategy=StrategySpec(
        graph=graph,
        signal_node="signal"
    ),
    execution=TradingExecutionSpec(
        mode="backtest",
        venue="binance",
        market_type="futures",
        latency_mode="INSTANT"
    )
)

# Run backtest
driver = TradingDriver.from_spec(spec)
driver.load_data(
    items=["BTC/USDT:USDT"],
    start="2024-01-01",
    end="2024-12-31"
)

for result in driver.run():
    print(f"PnL: {result.pnl:.2f} USDT")
5

Analyze results

View performance metrics:
# Get final metrics
metrics = driver.get_metrics()

print(f"Total Return: {metrics.total_return:.2%}")
print(f"Sharpe Ratio: {metrics.sharpe_ratio:.2f}")
print(f"Max Drawdown: {metrics.max_drawdown:.2%}")
print(f"Win Rate: {metrics.win_rate:.2%}")

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What’s Next?

Learn Core Concepts

Understand the ClyptQ architecture and ecosystem

Build Strategies

Dive deeper into strategy development

Operator Protocol

Learn about the core execution infrastructure

Trading System

Understand execution and risk management

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Need Help?

Documentation

Browse the complete documentation

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